Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "64"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 64 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 64, Node N06:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.228201 -0.138744 -1.240491 -0.506545 -0.879705 -1.053287 1.762781 -0.209339 0.5455 0.5367 0.3374 nan nan
2460014 not_connected 100.00% 0.00% 0.00% 0.00% - - -0.203733 -0.139249 -1.201540 -0.660767 -0.457624 -0.806111 4.745121 0.188214 0.5132 0.5005 0.3302 nan nan
2460013 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.393743 -0.374380 -1.186424 -0.628613 -0.855818 -1.033176 2.745347 0.231320 0.5399 0.5371 0.3443 nan nan
2460012 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.454630 -0.315685 -1.319066 -0.781806 -0.891584 -0.972315 1.856247 0.237040 0.5437 0.5395 0.3394 nan nan
2460011 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.019707 -0.098690 -1.308561 -1.178651 1.011227 -0.361483 1.223132 1.211418 0.5363 0.5370 0.3410 nan nan
2460010 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.161009 0.222102 -0.744915 -0.679634 -0.731866 -1.533479 0.348217 0.074598 0.5454 0.5503 0.3447 nan nan
2460009 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.426993 -0.187916 -1.049152 -0.589672 -0.547253 -0.994927 0.551849 0.267783 0.5505 0.5549 0.3500 nan nan
2460008 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.021033 0.331100 -0.977220 -0.768266 -0.391168 -0.906547 -0.016260 1.118681 0.6081 0.6154 0.3148 nan nan
2460007 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.146909 0.127729 -1.175037 -0.431134 -0.879407 -1.105404 3.075179 0.363492 0.5558 0.5586 0.3352 nan nan
2459999 not_connected 0.00% 99.50% 99.42% 0.00% - - nan nan nan nan nan nan nan nan 0.1557 0.1784 0.0930 nan nan
2459998 not_connected 100.00% 0.00% 0.00% 0.00% - - -0.137082 0.045602 -0.865972 -0.534806 -0.897052 -0.817817 5.505394 0.487532 0.5626 0.5588 0.3612 nan nan
2459997 not_connected 100.00% 0.00% 0.00% 0.00% - - -0.102581 -0.120982 -0.666412 -0.457180 -0.928435 -1.204872 6.379935 0.031313 0.5886 0.5847 0.3673 nan nan
2459996 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.193914 -0.077187 -0.935485 -0.395015 -0.734612 -1.220619 0.716497 0.729338 0.5842 0.5824 0.3831 nan nan
2459995 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.186435 -0.342572 -0.937923 -0.791279 -0.309561 -0.904570 1.343816 -0.024691 0.5858 0.5825 0.3676 nan nan
2459994 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.094144 -0.154208 -0.885418 -0.565475 -0.772352 -1.096523 1.199423 -0.659012 0.5785 0.5748 0.3620 nan nan
2459993 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.328078 -0.001825 -0.547435 -0.778322 -0.543276 -0.864250 1.574336 0.003403 0.5737 0.5891 0.3725 nan nan
2459991 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.208175 0.089580 -0.655724 -0.713106 -0.422601 -0.946819 0.884903 1.896906 0.5789 0.5648 0.3707 nan nan
2459990 not_connected 100.00% 0.00% 0.00% 0.00% - - 0.276532 0.166802 -0.819912 -0.780773 -0.644271 -0.710726 1.995555 5.492268 0.5735 0.5657 0.3676 nan nan
2459989 not_connected 100.00% 0.00% 0.00% 0.00% - - 0.085554 0.237588 -0.527754 -0.462720 -0.664296 -1.038264 1.319838 4.665341 0.5731 0.5661 0.3674 nan nan
2459988 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.151407 0.142124 -0.918501 -0.949399 -0.230488 -0.712782 2.443720 3.788848 0.5611 0.5549 0.3529 nan nan
2459987 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.254204 0.004332 -0.678139 -0.700589 -0.970438 -0.851019 0.725391 0.335022 0.5849 0.5771 0.3592 nan nan
2459986 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.140338 0.112824 -0.767338 -0.936046 -0.025915 -0.608897 1.986774 2.623773 0.5972 0.5999 0.3189 nan nan
2459985 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.109197 -0.193479 -0.836488 -0.743662 -0.663788 -1.335460 0.254890 -0.191588 0.5793 0.5737 0.3645 nan nan
2459984 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.375081 -0.220681 -0.695054 -0.724944 -1.178910 -1.342349 -0.359591 0.214625 0.5909 0.5886 0.3413 nan nan
2459983 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.025823 0.132620 -0.791500 -0.863992 0.855019 -0.007482 1.890766 3.284179 0.6145 0.6269 0.2917 nan nan
2459982 not_connected 0.00% 0.00% 0.00% 0.00% - - -1.286030 -0.460343 -1.173930 -0.408686 -0.331344 -0.356603 0.327478 1.622164 0.6425 0.6398 0.2920 nan nan
2459981 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.016514 0.311364 -0.699399 -1.024495 -0.608677 -0.164966 2.228528 0.201372 0.5739 0.5643 0.3604 nan nan
2459980 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.012947 0.067908 -0.838389 -0.902156 -0.798044 -1.227712 -0.164910 0.933253 0.6221 0.6186 0.3033 nan nan
2459979 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.080937 0.405570 -0.754490 -0.917646 -1.099648 -1.191760 1.280771 -0.447190 0.5691 0.5635 0.3608 nan nan
2459978 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.004953 0.300565 -0.721387 -1.009784 -0.559215 -0.891658 3.133456 0.044098 0.5666 0.5585 0.3690 nan nan
2459977 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.045752 0.213784 -0.759517 -0.851775 -0.754208 -1.385597 -0.022056 -0.181957 0.5391 0.5303 0.3259 nan nan
2459976 not_connected 0.00% 0.00% 0.00% 0.00% - - 0.102095 0.275375 -0.878119 -1.012455 -0.563159 -1.011153 1.941751 -0.304742 0.5811 0.5731 0.3631 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 64: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.762781 -0.138744 -0.228201 -0.506545 -1.240491 -1.053287 -0.879705 -0.209339 1.762781

Antenna 64: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 4.745121 -0.203733 -0.139249 -1.201540 -0.660767 -0.457624 -0.806111 4.745121 0.188214

Antenna 64: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 2.745347 -0.393743 -0.374380 -1.186424 -0.628613 -0.855818 -1.033176 2.745347 0.231320

Antenna 64: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.856247 -0.454630 -0.315685 -1.319066 -0.781806 -0.891584 -0.972315 1.856247 0.237040

Antenna 64: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.223132 0.019707 -0.098690 -1.308561 -1.178651 1.011227 -0.361483 1.223132 1.211418

Antenna 64: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 0.348217 0.161009 0.222102 -0.744915 -0.679634 -0.731866 -1.533479 0.348217 0.074598

Antenna 64: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 0.551849 -0.426993 -0.187916 -1.049152 -0.589672 -0.547253 -0.994927 0.551849 0.267783

Antenna 64: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 1.118681 0.331100 0.021033 -0.768266 -0.977220 -0.906547 -0.391168 1.118681 -0.016260

Antenna 64: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 3.075179 -0.146909 0.127729 -1.175037 -0.431134 -0.879407 -1.105404 3.075179 0.363492

Antenna 64: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Shape nan nan nan nan nan nan nan nan nan

Antenna 64: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 5.505394 -0.137082 0.045602 -0.865972 -0.534806 -0.897052 -0.817817 5.505394 0.487532

Antenna 64: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 6.379935 -0.102581 -0.120982 -0.666412 -0.457180 -0.928435 -1.204872 6.379935 0.031313

Antenna 64: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 0.729338 -0.193914 -0.077187 -0.935485 -0.395015 -0.734612 -1.220619 0.716497 0.729338

Antenna 64: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.343816 -0.186435 -0.342572 -0.937923 -0.791279 -0.309561 -0.904570 1.343816 -0.024691

Antenna 64: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.199423 -0.094144 -0.154208 -0.885418 -0.565475 -0.772352 -1.096523 1.199423 -0.659012

Antenna 64: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.574336 0.328078 -0.001825 -0.547435 -0.778322 -0.543276 -0.864250 1.574336 0.003403

Antenna 64: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 1.896906 0.208175 0.089580 -0.655724 -0.713106 -0.422601 -0.946819 0.884903 1.896906

Antenna 64: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 5.492268 0.166802 0.276532 -0.780773 -0.819912 -0.710726 -0.644271 5.492268 1.995555

Antenna 64: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 4.665341 0.237588 0.085554 -0.462720 -0.527754 -1.038264 -0.664296 4.665341 1.319838

Antenna 64: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 3.788848 0.142124 0.151407 -0.949399 -0.918501 -0.712782 -0.230488 3.788848 2.443720

Antenna 64: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 0.725391 -0.254204 0.004332 -0.678139 -0.700589 -0.970438 -0.851019 0.725391 0.335022

Antenna 64: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 2.623773 0.112824 0.140338 -0.936046 -0.767338 -0.608897 -0.025915 2.623773 1.986774

Antenna 64: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 0.254890 -0.193479 -0.109197 -0.743662 -0.836488 -1.335460 -0.663788 -0.191588 0.254890

Antenna 64: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 0.214625 -0.375081 -0.220681 -0.695054 -0.724944 -1.178910 -1.342349 -0.359591 0.214625

Antenna 64: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 3.284179 -0.025823 0.132620 -0.791500 -0.863992 0.855019 -0.007482 1.890766 3.284179

Antenna 64: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 1.622164 -1.286030 -0.460343 -1.173930 -0.408686 -0.331344 -0.356603 0.327478 1.622164

Antenna 64: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 2.228528 0.311364 -0.016514 -1.024495 -0.699399 -0.164966 -0.608677 0.201372 2.228528

Antenna 64: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Temporal Discontinuties 0.933253 0.067908 -0.012947 -0.902156 -0.838389 -1.227712 -0.798044 0.933253 -0.164910

Antenna 64: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.280771 0.080937 0.405570 -0.754490 -0.917646 -1.099648 -1.191760 1.280771 -0.447190

Antenna 64: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 3.133456 0.300565 0.004953 -1.009784 -0.721387 -0.891658 -0.559215 0.044098 3.133456

Antenna 64: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
64 N06 not_connected nn Shape 0.213784 0.045752 0.213784 -0.759517 -0.851775 -0.754208 -1.385597 -0.022056 -0.181957

Antenna 64: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
64 N06 not_connected ee Temporal Discontinuties 1.941751 0.275375 0.102095 -1.012455 -0.878119 -1.011153 -0.563159 -0.304742 1.941751
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